The release of the Autism Brain Imaging Data Exchange (ABIDE) repository in August 2012 marked a milestone for the neuroimaging of autism spectrum disorders (ASD). This grass-roots initiative has generated an unprecedented, open sample of ASD neuroimaging data by aggregating and openly sharing resting state fMRI (R-fMRI), structural MRI, as well as phenotypic data previously collected from over 1100 individuals (539 with ASD and 573 sex- and age-matched typical controls (TC)) from 17 international sites. Feasibility analyses performed by the ABIDE consortium demonstrated the ability to successfully carry out exploration with such an aggregate dataset. Nevertheless, due to the complexity of the functional connectome and the substantial heterogeneity of ASD, larger and better-characterized samples are critical for effective and transformative discovery. Here, we aim to enhance the utility of the ABIDE resource and the innovation and significance of the questions it can address by increasing both its size (to at least twice as many datasets as in the original repository) and the breadth of the phenotypic data shared. First, an expanded repository will allow for the unprecedented performance of whole-brain functional connectivity group comparisons (ASD vs. TC) in two carefully matched split samples. We expect that the group differences emerging in both samples (i.e., the exploratory and discovery split-samples) will robustly represent the core neurophysiological correlates of ASD. Second, the expansion will increase the sample of females with ASD, who are usually drastically underrepresented in studies with smaller sample sizes. Proposed analyses will reveal properties of the intrinsic functional architecture of the ASD female brain, which, to date, remain completely unknown. Understanding sex differences in the neural substrates of ASD will provide insights into their underpinnings and consequently, into possible protective factors. Finally, the enhanced dataset will facilitate explorations of brain-behavior relationships, such as those relevant to the neurona correlates of psychiatric comorbidity in ASD. Specifically, primary analyses will focus on ADHD symptom ratings. At the same time, other measures of psychopathology included in the expansion of phenotypic data provided by this open sharing repository, will enable users to conduct further explorations. This high-risk, high-reward strategy has the potential to serve as a crucial linkage between clinical and brain phenotypes, and eventually extend to genetic and epigenetic applications. Thus, this novel exploratory project is high impact for a relatively minor investment. As with genetic discovery, where the strategy of data aggregation and open sharing has proven to be fruitful, this project will offer, within a short time frame, a unique and unprecedented resource: the results of analyses will form the basis for future targeted investigations into the complex neurobiological mechanisms underlying ASD.